vertex-ai-endpoint-config
Vertex Ai Endpoint Config - Auto-activating skill for GCP Skills. Triggers on: vertex ai endpoint config, vertex ai endpoint config Part of the GCP Skills skill category.
36
Quality
3%
Does it follow best practices?
Impact
99%
1.03xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/14-gcp-skills/vertex-ai-endpoint-config/SKILL.mdQuality
Discovery
7%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is severely underdeveloped, functioning more as a label than a useful skill description. It provides no information about what capabilities the skill offers, what actions it can perform, or when Claude should use it. The redundant trigger terms and boilerplate 'Auto-activating skill' language add no value for skill selection.
Suggestions
Add specific actions the skill performs, e.g., 'Configure Vertex AI endpoints for model deployment, set traffic splitting, manage autoscaling policies, and update endpoint settings.'
Include a 'Use when...' clause with natural trigger terms like 'Use when deploying ML models to GCP, configuring inference endpoints, setting up model serving, or managing Vertex AI deployments.'
Add variations of trigger terms users might naturally say: 'model deployment', 'inference endpoint', 'serve model', 'GCP ML', 'prediction endpoint', 'online prediction'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions - only mentions 'Vertex AI endpoint config' without explaining what actions can be performed (create, modify, deploy, configure, etc.). | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond naming the topic, and has no explicit 'Use when...' clause or equivalent guidance for when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | The trigger terms are redundant ('vertex ai endpoint config' listed twice) and miss natural variations users might say like 'deploy model', 'endpoint deployment', 'model serving', 'inference endpoint', or 'GCP ML deployment'. | 1 / 3 |
Distinctiveness Conflict Risk | While 'Vertex AI endpoint' is somewhat specific to a GCP service, the lack of detail about what operations it covers could cause overlap with other GCP or ML deployment skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill content is an empty template that provides zero actionable information about Vertex AI endpoint configuration. It consists entirely of generic boilerplate text that could apply to any skill, with no actual technical content, code examples, commands, or specific guidance for GCP Vertex AI endpoints.
Suggestions
Add concrete gcloud CLI commands or Terraform/Python code for creating and configuring Vertex AI endpoints (e.g., `gcloud ai endpoints create --display-name=...`)
Include a clear workflow with steps: create endpoint, deploy model, configure traffic split, validate deployment
Provide specific configuration examples showing endpoint settings like machine type, min/max replicas, and autoscaling policies
Add validation steps such as checking endpoint status with `gcloud ai endpoints describe` and testing predictions
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely boilerplate with no actual technical information about Vertex AI endpoint configuration. It explains what the skill does in abstract terms without providing any concrete guidance, wasting tokens on meta-description. | 1 / 3 |
Actionability | No concrete code, commands, or specific instructions are provided. The content only describes what the skill claims to do ('provides step-by-step guidance') without actually providing any guidance, examples, or executable content. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps, no sequence, and no validation checkpoints for configuring Vertex AI endpoints. The phrase 'step-by-step guidance' is mentioned but never delivered. | 1 / 3 |
Progressive Disclosure | The content is a flat, uninformative structure with no references to detailed documentation, no links to related files, and no organization of content by complexity or use case. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
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- Reviewed
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